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Criar a versão específica de uma instância
Nesta página, descrevemos como criar uma versão específica de uma
instância do Vertex AI Workbench.
Por que criar uma versão específica
Para garantir que a instância do Vertex AI Workbench tenha software
compatível com o código ou o aplicativo, crie
uma versão específica.
As imagens de instância do Vertex AI Workbench são atualizadas com frequência, e
versões específicas de software e pacotes pré-instalados variam de acordo com
a versão.
Depois de criar uma versão específica de
uma instância do Vertex AI Workbench, será possível fazer upgrade dela.
O upgrade da instância atualiza o software e os pacotes pré-instalados.
Para mais informações,
consulte Fazer upgrade do ambiente de uma instância.
Antes de começar
Sign in to your Google Cloud account. If you're new to
Google Cloud,
create an account to evaluate how our products perform in
real-world scenarios. New customers also get $300 in free credits to
run, test, and deploy workloads.
In the Google Cloud console, on the project selector page,
select or create a Google Cloud project.
É possível criar uma versão específica de uma instância do Vertex AI Workbench usando o console Google Cloud ou a Google Cloud CLI.
Console
Para criar uma versão específica de uma instância do Vertex AI Workbench,
faça o seguinte:
Ao criar uma instância,
na seção Ambiente, selecione Usar uma versão anterior.
Clique na lista Versão e selecione uma versão. As versões são numeradas
na forma de M seguida pelo número da versão,
por exemplo, M123.
Preencha o restante da caixa de diálogo de criação de instância
e clique em Criar.
O Vertex AI Workbench cria uma instância e a inicia automaticamente.
Quando a instância estiver pronta para uso, o Vertex AI Workbench
ativa um link Abrir JupyterLab.
gcloud
Antes de usar os dados do comando abaixo, faça estas substituições:
INSTANCE_NAME: o nome da sua instância do Vertex AI Workbench. Precisa começar com uma letra seguida por até 62 letras minúsculas, números ou hifens (-) e não pode terminar com um hífen.
PROJECT_ID: ID do projeto;
LOCATION: a zona em que você quer que a instância esteja localizada
VM_IMAGE_NAME: o nome da imagem. Para conferir uma lista dos nomes de imagens disponíveis, use o comando get-config.
METADATA: metadados personalizados a serem aplicados a esta instância. Por exemplo, para especificar um script pós-inicialização, use a tag de metadados post-startup-script no formato: --metadata=post-startup-script=gs://BUCKET_NAME/hello.sh
Para mais informações sobre o comando para criar uma
instância usando a linha de comando, consulte a documentação
da CLI gcloud.
O Vertex AI Workbench cria uma instância e a inicia automaticamente.
Quando a instância estiver pronta para uso, o Vertex AI Workbench
ativa um link Abrir JupyterLab no console Google Cloud .
[[["Fácil de entender","easyToUnderstand","thumb-up"],["Meu problema foi resolvido","solvedMyProblem","thumb-up"],["Outro","otherUp","thumb-up"]],[["Difícil de entender","hardToUnderstand","thumb-down"],["Informações incorretas ou exemplo de código","incorrectInformationOrSampleCode","thumb-down"],["Não contém as informações/amostras de que eu preciso","missingTheInformationSamplesINeed","thumb-down"],["Problema na tradução","translationIssue","thumb-down"],["Outro","otherDown","thumb-down"]],["Última atualização 2025-08-19 UTC."],[],[],null,["# Create a specific version of a Vertex AI Workbench instance\n\nCreate a specific version of an instance\n========================================\n\nThis page describes how to create a specific version of a\nVertex AI Workbench instance.\n\nWhy you might want to create a specific version\n-----------------------------------------------\n\nTo ensure that your Vertex AI Workbench instance has software\nthat is compatible with your code or application, you might want to create\na specific version.\n\nVertex AI Workbench instance images are updated frequently, and\nspecific versions of preinstalled software and packages vary from version\nto version.\n\nTo learn more about specific Vertex AI Workbench versions,\nsee the [Vertex AI release notes](/vertex-ai/docs/release-notes).\n\nAfter you create a specific version of\na Vertex AI Workbench instance, you can upgrade it.\nUpgrading the instance updates the preinstalled software and packages.\nFor more information,\nsee [Upgrade an instance's environment](/vertex-ai/docs/workbench/instances/upgrade).\n\nBefore you begin\n----------------\n\n- Sign in to your Google Cloud account. If you're new to Google Cloud, [create an account](https://console.cloud.google.com/freetrial) to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.\n- In the Google Cloud console, on the project selector page,\n select or create a Google Cloud project.\n\n | **Note**: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.\n\n [Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n-\n [Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n-\n\n\n Enable the Notebooks API.\n\n\n [Enable the API](https://console.cloud.google.com/flows/enableapi?apiid=notebooks.googleapis.com&redirect=https://console.cloud.google.com)\n\n- In the Google Cloud console, on the project selector page,\n select or create a Google Cloud project.\n\n | **Note**: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.\n\n [Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n-\n [Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n-\n\n\n Enable the Notebooks API.\n\n\n [Enable the API](https://console.cloud.google.com/flows/enableapi?apiid=notebooks.googleapis.com&redirect=https://console.cloud.google.com)\n\n\u003cbr /\u003e\n\nCreate a specific version\n-------------------------\n\nYou can create a specific version of a Vertex AI Workbench instance\nby using the Google Cloud console or the Google Cloud CLI. \n\n### Console\n\nTo create a specific version of a Vertex AI Workbench instance,\ndo the following:\n\n1. When you [create an instance](/vertex-ai/docs/workbench/instances/create),\n in the **Environment** section, select **Use a previous version**.\n\n2. Click the **Version** list, and select a version. Versions are numbered\n in the form of an `M` followed by the number of the release,\n for example, `M123`.\n\n3. Complete the rest of the instance-creation dialog, and then\n click **Create**.\n\n Vertex AI Workbench creates an instance and automatically starts it.\n When the instance is ready to use, Vertex AI Workbench\n activates an **Open JupyterLab** link.\n\n### gcloud\n\n\nBefore using any of the command data below,\nmake the following replacements:\n\n- \u003cvar translate=\"no\"\u003eINSTANCE_NAME\u003c/var\u003e: the name of your Vertex AI Workbench instance; must start with a letter followed by up to 62 lowercase letters, numbers, or hyphens (-), and cannot end with a hyphen\n- \u003cvar translate=\"no\"\u003ePROJECT_ID\u003c/var\u003e: your project ID\n- \u003cvar translate=\"no\"\u003eLOCATION\u003c/var\u003e: the zone where you want your instance to be located\n- \u003cvar translate=\"no\"\u003eVM_IMAGE_NAME\u003c/var\u003e: the image name; to get a list of the available image names, use the [`get-config`\n command](/sdk/gcloud/reference/workbench/instances/get-config)\n- \u003cvar translate=\"no\"\u003eMACHINE_TYPE\u003c/var\u003e: the [machine type](/compute/docs/machine-resource) of your instance's VM\n- \u003cvar translate=\"no\"\u003eMETADATA\u003c/var\u003e: custom metadata to apply to this instance;\n for example, to specify a post-startup-script,\n you can use the `post-startup-script` metadata tag, in the format:\n `--metadata=post-startup-script=gs://`\u003cvar translate=\"no\"\u003eBUCKET_NAME\u003c/var\u003e`/hello.sh`\n\n | To enable the JupyterLab 4 preview, use `--metadata=enable-jupyterlab4-preview=true`. For more information, see [JupyterLab 4 preview](/vertex-ai/docs/workbench/instances/create#jupyterlab-preview).\n\n\nExecute the\n\nfollowing\n\ncommand:\n\n#### Linux, macOS, or Cloud Shell\n\n**Note:** Ensure you have initialized the Google Cloud CLI with authentication and a project by running either [gcloud init](/sdk/gcloud/reference/init); or [gcloud auth login](/sdk/gcloud/reference/auth/login) and [gcloud config set project](/sdk/gcloud/reference/config/set). \n\n```bash\ngcloud workbench instances create INSTANCE_NAME \\\n --project=PROJECT_ID \\\n --location=LOCATION \\\n --vm-image-project=\"cloud-notebooks-managed\" \\\n --vm-image-name=VM_IMAGE_NAME \\\n --machine-type=MACHINE_TYPE \\\n --metadata=METADATA\n```\n\n#### Windows (PowerShell)\n\n**Note:** Ensure you have initialized the Google Cloud CLI with authentication and a project by running either [gcloud init](/sdk/gcloud/reference/init); or [gcloud auth login](/sdk/gcloud/reference/auth/login) and [gcloud config set project](/sdk/gcloud/reference/config/set). \n\n```bash\ngcloud workbench instances create INSTANCE_NAME `\n --project=PROJECT_ID `\n --location=LOCATION `\n --vm-image-project=\"cloud-notebooks-managed\" `\n --vm-image-name=VM_IMAGE_NAME `\n --machine-type=MACHINE_TYPE `\n --metadata=METADATA\n```\n\n#### Windows (cmd.exe)\n\n**Note:** Ensure you have initialized the Google Cloud CLI with authentication and a project by running either [gcloud init](/sdk/gcloud/reference/init); or [gcloud auth login](/sdk/gcloud/reference/auth/login) and [gcloud config set project](/sdk/gcloud/reference/config/set). \n\n```bash\ngcloud workbench instances create INSTANCE_NAME ^\n --project=PROJECT_ID ^\n --location=LOCATION ^\n --vm-image-project=\"cloud-notebooks-managed\" ^\n --vm-image-name=VM_IMAGE_NAME ^\n --machine-type=MACHINE_TYPE ^\n --metadata=METADATA\n```\n\n\u003cbr /\u003e\n\nFor more information about the command for creating an\ninstance from the command line, see the [gcloud CLI\ndocumentation](/sdk/gcloud/reference/workbench/instances/create).\n\nVertex AI Workbench creates an instance and automatically starts it.\nWhen the instance is ready to use, Vertex AI Workbench\nactivates an **Open JupyterLab** link in the Google Cloud console.\n\nWhat's next\n-----------\n\n- Learn more about [upgrading\n Vertex AI Workbench instances](/vertex-ai/docs/workbench/instances/upgrade)\n to ensure that your instance upgrades only when you are ready.\n\n- Learn about [monitoring the health status](/vertex-ai/docs/workbench/instances/monitor-health) of\n your Vertex AI Workbench instance."]]
